Mike Abbott

Partner, Kleiner Perkins · 1 appearance on the record.

computed by AI from the episodes · how this works → · full disclaimer →

14statements → 9claims → 3claims resolved → 67%fully supported → 3.36/5average certainty → 2/5average debate potential → ≈4.0/5argument clarity, estimated →

2 supported 0 partly supported 1 contradicted 6 not checkable as stated how the 9 claims stand · each chip opens the sources

5 predictions · 4 assertions · 2 opinions · 2 insights · 1 disclosure · every statement was checked. The predictions and assertions are the 9 claims: statements the public record can support or contradict. 3 are resolved, and 6 name no date, number or outcome precise enough to check. Everything else (opinions, insights, what ifs, disclosures) can never be settled by the record, so it carries no assessment.

The record, in short

What the tape says about how Mike argues and how the claims held up. Everything they said, and everything said about them, is in the tabs below.

Their most notable supported claim

Assertion Supported

Kleiner Perkins' largest investment check ever was into Twitter

“The largest check that the KP's ever written was in the Twitter.”

Mike Abbott Oct 16, 2014 ▶ 2:34 Mike Abbott, KPCB // Data Driven #30 // Oct 2014 (Hosted by FirstMark Capital)

Their most notable contradicted claim

Prediction Didn’t hold up

Most data growth to 40 zettabytes by 2020 will originate from sensors

“If you look at the, you know, the forecasts that are going from the 2.8 zettabytes to 40 zettabytes in 2020 that's, most of that data is gonna be coming from sensors, right?”

Mike Abbott Oct 16, 2014 ▶ 17:01 Mike Abbott, KPCB // Data Driven #30 // Oct 2014 (Hosted by FirstMark Capital)

How they sound: speaking style how? →

274 words/min while actually speaking · 25.4 um and uh per 1k words

No argument clarity score for Mike Abbott: only 4 usable question→answer exchanges on raw tape (a fair score needs 8+). We do not score a sample that small. Roundtable and news formats yield far fewer direct exchanges than interviews. Their coarse estimate from 4 raw tape exchanges is ≈4.0/5, shown at half point precision because the sample is small.

Measured by listening to the audio itself: 3,703 words across 1 episode of raw-level tape, transcribed verbatim with every um and uh kept, each one attributed only where the alignment onto our timed stream is unambiguous. These are measurements of speaking style. We do not rank them: across this corpus, fluency and argument quality are nearly uncorrelated (ρ≈0.2), and smooth talking does not signal clear thinking. How it's measured →

What they said14 Episodes1

Everything Mike Abbott said on the MAD Podcast that made the record, most notable first. Filter by type, assessment or year in the ledger →

Prediction Not checkable as stated

Big tech companies, not startups, will drive machine learning innovations

“I think we're gonna probably be seeing innovations from those types of companies, ah, before startups.”

Mike Abbott Oct 16, 2014 ▶ 18:53 Mike Abbott, KPCB // Data Driven #30 // Oct 2014 (Hosted by FirstMark Capital)

Prediction Not checkable as stated

Data analytics startups will eventually dislodge incumbents like SAS

“I do think that the incumbent players like SAS I mean, I think over time will hopefully be dislodged by, you know, some number of startups.”

Mike Abbott Oct 16, 2014 ▶ 12:26 Mike Abbott, KPCB // Data Driven #30 // Oct 2014 (Hosted by FirstMark Capital)

Assertion Supported

Kleiner Perkins' largest investment check ever was into Twitter

“The largest check that the KP's ever written was in the Twitter.”

Mike Abbott Oct 16, 2014 ▶ 2:34 Mike Abbott, KPCB // Data Driven #30 // Oct 2014 (Hosted by FirstMark Capital)

Insight

Cheap storage causes enterprise and consumer companies to suffer from data obesity

“The cost and ability to store tons of data is, is so prevalent both in consumer and enterprise companies that I think oftentimes you end up in this kind of data obesity state where you start storing data for reasons you don't even know why you're storing it.”

Mike Abbott Oct 16, 2014 ▶ 2:48 Mike Abbott, KPCB // Data Driven #30 // Oct 2014 (Hosted by FirstMark Capital)

Prediction Not checkable as stated

Large enterprise companies will eventually move production workloads onto Hadoop

“I think it will happen.”

Mike Abbott Oct 16, 2014 ▶ 4:01 Mike Abbott, KPCB // Data Driven #30 // Oct 2014 (Hosted by FirstMark Capital)

Assertion Supported

Kaggle competition winners rely primarily on feature engineering and algorithm ensembles

“If you look at, you know, who wins most of the Kaggle competitions, it tends to be, you know, combinations of ensembles of different algorithms, but it's really the feature engineering.”

Mike Abbott Oct 16, 2014 ▶ 5:03 Mike Abbott, KPCB // Data Driven #30 // Oct 2014 (Hosted by FirstMark Capital)

Assertion Not checkable as stated

US government intelligence agencies were using big data software in 2004

“We had three-letter agencies using our software 10 years ago, like, plus, and they certainly had more than big data, so it's not new.”

Mike Abbott Oct 16, 2014 ▶ 7:28 Mike Abbott, KPCB // Data Driven #30 // Oct 2014 (Hosted by FirstMark Capital)

Opinion

Differentiating big data startups purely on data visualization is getting difficult

“It just feels like between D three and other tools, that that area, it's getting more difficult to differentiate just on visualization. You have to have other pieces.”

Mike Abbott Oct 16, 2014 ▶ 10:28 Mike Abbott, KPCB // Data Driven #30 // Oct 2014 (Hosted by FirstMark Capital)

Prediction Not checkable as stated

Data science will always require specialized professionals with strong statistics backgrounds

“I think there's always going to be a need for someone who has a background in statistics and can understand how to use tools to understand what are the questions that should be asked, how to do the feature engineering, to understand your business, whether it b…”

Mike Abbott Oct 16, 2014 ▶ 12:10 Mike Abbott, KPCB // Data Driven #30 // Oct 2014 (Hosted by FirstMark Capital)

Insight

Big data startups greatly underestimate the requirements for enterprise readiness

“I think that in general, I try to determine does this team have a strong enough understanding of what it's like to sell to the Fortune 2000 or 5000 to know what it means to be enterprise ready? I think that oftentimes, ah, companies greatly underestimate that.”

Mike Abbott Oct 16, 2014 ▶ 14:50 Mike Abbott, KPCB // Data Driven #30 // Oct 2014 (Hosted by FirstMark Capital)

Disclosure

Kleiner Perkins passes on founders who cannot justify their tech stack choices

“And I'm not saying that the decisions that that company made were wrong, necessarily, but I think that at the end of the day, technology is here to solve a problem, and if you don't know why you selected a particular, For particular, particular technology, I t…”

Mike Abbott Oct 16, 2014 ▶ 15:57 Mike Abbott, KPCB // Data Driven #30 // Oct 2014 (Hosted by FirstMark Capital)

Prediction Didn’t hold up

Most data growth to 40 zettabytes by 2020 will originate from sensors

“If you look at the, you know, the forecasts that are going from the 2.8 zettabytes to 40 zettabytes in 2020 that's, most of that data is gonna be coming from sensors, right?”

Mike Abbott Oct 16, 2014 ▶ 17:01 Mike Abbott, KPCB // Data Driven #30 // Oct 2014 (Hosted by FirstMark Capital)

Assertion Not checkable as stated

Companies mine consumer property data to identify B2B lead generation opportunities

“Insurance, you know, homes, there's all this, like, if you look at the statistics of, okay, marriage is oftentimes nine months past that, like, you know, different regions of the country, you could also predict maybe when they go buy a home, and so actually, l…”

Mike Abbott Oct 16, 2014 ▶ 21:42 Mike Abbott, KPCB // Data Driven #30 // Oct 2014 (Hosted by FirstMark Capital)

Opinion

Enterprise data lineage and SOX compliance remain major open opportunity areas

“I think that's a, Still, like, a big open area on, in the lineage side, especially when you start linking into things around, like, SOX compliance, and, like, what does that actually mean?”

Mike Abbott Oct 16, 2014 ▶ 10:42 Mike Abbott, KPCB // Data Driven #30 // Oct 2014 (Hosted by FirstMark Capital)

Appearances (1)

Episode	Date	Speaking time
Mike Abbott, KPCB // Data Driven #30 // Oct 2014 (Hosted by FirstMark Capital)	Oct 16, 2014	16m

Mike Abbott

The record, in short

Their most notable supported claim

Their most notable contradicted claim

How they sound: speaking style how? →

Appearances (1)

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